IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v119y2019icp118-125.html
   My bibliography  Save this article

Analysis of SIR epidemic model with information spreading of awareness

Author

Listed:
  • Kabir, K.M. Ariful
  • Kuga, Kazuki
  • Tanimoto, Jun

Abstract

The information spreading of awareness can prompt the manners of human to ease the infectious possibility and assist to recover swiftly. A dynamic system of Susceptible-Infected-Recovered (SIR) with Unaware-Aware (UA) process (SIR-UA) is newly developed by using compartment model through analytical approach with assumption of an infinite and well-mixed population. Moreover, individuals in a population can be classified into six states as unaware susceptible(SU), aware susceptible(SA), unaware infected(IU), aware infected(IA), unaware recovered(RU), and aware recovered(RA). Compared with previous models, the new dynamic set of equations described the more widespread situation and incorporated all possible states of Unaware-Aware (UA) with SIR process. The effect of awareness is explored carefully to show the significance on epidemic model with time steps. Consequently, the properties of parameters on the epidemic awareness model are studied to deliberate different physical situations. Finally, full phase diagrams are explored to show the epidemic sizes of susceptible and recovered individuals for various parameters.

Suggested Citation

  • Kabir, K.M. Ariful & Kuga, Kazuki & Tanimoto, Jun, 2019. "Analysis of SIR epidemic model with information spreading of awareness," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 118-125.
  • Handle: RePEc:eee:chsofr:v:119:y:2019:i:c:p:118-125
    DOI: 10.1016/j.chaos.2018.12.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077918303898
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2018.12.017?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Huo, Liang’an & Song, Naixiang, 2016. "Dynamical interplay between the dissemination of scientific knowledge and rumor spreading in emergency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 73-84.
    2. Gao, Bo & Deng, Zhenghong & Zhao, Dawei, 2016. "Competing spreading processes and immunization in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 93(C), pages 175-181.
    3. Fan, Chong-jun & Jin, Yang & Huo, Liang-an & Liu, Chen & Yang, Yun-peng & Wang, Ya-qiong, 2016. "Effect of individual behavior on the interplay between awareness and disease spreading in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 523-530.
    4. Avner Ahituv & V. Joseph Hotz & Tomas Philipson, 1996. "The Responsiveness of the Demand for Condoms to the Local Prevalence of AIDS," Journal of Human Resources, University of Wisconsin Press, vol. 31(4), pages 869-897.
    5. Dantas, Eber & Tosin, Michel & Cunha Jr, Americo, 2018. "Calibration of a SEIR–SEI epidemic model to describe the Zika virus outbreak in Brazil," Applied Mathematics and Computation, Elsevier, vol. 338(C), pages 249-259.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jamie Bedson & Laura A. Skrip & Danielle Pedi & Sharon Abramowitz & Simone Carter & Mohamed F. Jalloh & Sebastian Funk & Nina Gobat & Tamara Giles-Vernick & Gerardo Chowell & João Rangel Almeida & Ran, 2021. "A review and agenda for integrated disease models including social and behavioural factors," Nature Human Behaviour, Nature, vol. 5(7), pages 834-846, July.
    2. Kabir, K.M. Ariful & Tanimoto, Jun, 2019. "Dynamical behaviors for vaccination can suppress infectious disease – A game theoretical approach," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 229-239.
    3. Giulietti, Corrado & Vlassopoulos, Michael & Zenou, Yves, 2021. "When Reality Bites: Local Deaths and Vaccine Take-Up," GLO Discussion Paper Series 999, Global Labor Organization (GLO).
    4. Kai Barron & Luis F. Gamboa & Paul Rodríguez-Lesmes, 2019. "Behavioural Response to a Sudden Health Risk: Dengue and Educational Outcomes in Colombia," Journal of Development Studies, Taylor & Francis Journals, vol. 55(4), pages 620-644, April.
    5. Hussey, Andrew & Nikolsko-Rzhevskyy, Alex & Walker, Jay, 2010. "AIDing Contraception: HIV and Recent Trends in Abortion Rates," MPRA Paper 20895, University Library of Munich, Germany.
    6. Zhu, Hongmiao & Jin, Zhen & Yan, Xin, 2023. "A dynamics model of coupling transmission for multiple different knowledge in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    7. Battiston, Pietro & Gamba, Simona, 2021. "COVID-19: R0 is lower where outbreak is larger," Health Policy, Elsevier, vol. 125(2), pages 141-147.
    8. Toxvaerd, Flavio, 2010. "Recurrent Infection and Externalities in Prevention," CEPR Discussion Papers 8112, C.E.P.R. Discussion Papers.
    9. Zhang, Yaming & Su, Yanyuan & Weigang, Li & Liu, Haiou, 2019. "Interacting model of rumor propagation and behavior spreading in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 121(C), pages 168-177.
    10. Pronkina, Elizaveta & Berniell, Inés & Fawaz, Yarine & Laferrère, Anne & Mira, Pedro, 2023. "The COVID-19 curtain: Can past communist regimes explain the vaccination divide in Europe?," Social Science & Medicine, Elsevier, vol. 321(C).
    11. Daniel S. Hamermesh, 1999. "The Art of Labormetrics," NBER Working Papers 6927, National Bureau of Economic Research, Inc.
    12. Yunhwan Kim & Ana Vivas Barber & Sunmi Lee, 2020. "Modeling influenza transmission dynamics with media coverage data of the 2009 H1N1 outbreak in Korea," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-21, June.
    13. Pierluigi Diotaiuti & Giuseppe Valente & Stefania Mancone & Lavinia Falese & Fernando Bellizzi & Daniela Anastasi & Elisa Langiano & Fábio Hech Dominski & Alexandro Andrade, 2021. "Perception of Risk, Self-Efficacy and Social Trust during the Diffusion of Covid-19 in Italy," IJERPH, MDPI, vol. 18(7), pages 1-17, March.
    14. Zhu, Yu-Xiao & Cao, Yan-Yan & Chen, Ting & Qiu, Xiao-Yan & Wang, Wei & Hou, Rui, 2018. "Crossover phenomena in growth pattern of social contagions with restricted contact," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 408-414.
    15. Matthew Goodkin-Gold & Michael Kremer & Christopher M. Snyder & Heidi L. Williams, 2020. "Optimal Vaccine Subsidies for Endemic and Epidemic Diseases," Working Papers 2020-162, Becker Friedman Institute for Research In Economics.
    16. Kai Barron & Charles D. H. Parry & Debbie Bradshaw & Rob Dorrington & Pam Groenewald & Ria Laubscher & Richard Matzopoulos, 2024. "Alcohol, Violence, and Injury-Induced Mortality: Evidence from a Modern-Day Prohibition," The Review of Economics and Statistics, MIT Press, vol. 106(4), pages 938-955, July.
    17. Celidoni, Martina & Costa-Font, Joan & Salmasi, Luca, 2023. "Mobility restrictions and alcohol use during lockdown: “A still and dry pandemic for the many”?," Economics & Human Biology, Elsevier, vol. 50(C).
    18. Alison L. Sexton Ward & Timothy K. M. Beatty, 2016. "Who Responds to Air Quality Alerts?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 65(2), pages 487-511, October.
    19. Noel Rapa, 2021. "Mitigation measures, prevalence response and public mobility during the COVID-19 emergency," CBM Working Papers WP/03/2021, Central Bank of Malta.
    20. Phillip B. Levine, 2001. "The Sexual Activity and Birth-Control Use of American Teenagers," NBER Chapters, in: Risky Behavior among Youths: An Economic Analysis, pages 167-218, National Bureau of Economic Research, Inc.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:119:y:2019:i:c:p:118-125. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.